Machine Learning Analysis for Phenolic Compound Monitoring Using a Mobile Phone-Based ECL Sensor

Machine learning (ML) can be an appropriate approach to overcoming common problems associated with sensors for low-cost, point-of-care diagnostics, such as non-linearity, multidimensionality, sensor-to-sensor variations, presence of anomalies, and ambiguity in key features. This study proposes a nov...

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Detalles Bibliográficos
Autores principales: Taylor, Joseph, Ccopa-Rivera, Elmer, Kim, Solomon, Campbell, Reise, Summerscales, Rodney, Kwon, Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473430/
https://www.ncbi.nlm.nih.gov/pubmed/34577213
http://dx.doi.org/10.3390/s21186004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473430/
https://www.ncbi.nlm.nih.gov/pubmed/34577213
http://dx.doi.org/10.3390/s21186004

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